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Birantx

polymarket-mcp-server

by Birantx

Get Polymarket price history

get_price_history

Retrieve historical mid-price time series for a prediction market outcome token. Get summary statistics (first, last, min, max, change) and raw data points, with automatic downsampling for compact responses.

Instructions

Historical mid-price time series for one outcome token. Returns summary stats (first/last/min/max, change) plus the raw points (Unix seconds t, probability p). Large series are downsampled to keep responses compact.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenIdYesCLOB token ID of the outcome to chart
intervalNoLook-back window (default '1w')
fidelityNoResolution in minutes between data points (e.g. 60 = hourly). Defaults per interval if omitted.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses that large series are downsampled to keep responses compact, and mentions the return format (summary stats + raw points). This is transparent about behavior, though it could mention authentication or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no wasted words, clearly front-loaded with the core purpose. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 3 parameters, no output schema, and moderate complexity, the description covers the essential aspects (what is returned, summary stats, raw points, downsampling). It is complete enough for an agent to understand usage, though some might want more detail on output structure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed descriptions, so the description adds limited extra value. The mention of downsampling relates to fidelity but does not significantly enhance understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it provides 'Historical mid-price time series for one outcome token' with summary stats and raw points, distinguishing it from siblings like get_market or get_orderbook which serve different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains what the tool does but does not explicitly state when to use it vs alternatives or when not to use it. The context is clear, but no exclusions or alternative guidance is given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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